The 20th European Workshop on Periodontology (2024) brought together experts to evaluate the latest in periodontal diagnostics, focusing on traditional methods, biomarkers, and emerging technologies like AI. Here’s a breakdown of the key takeaways:

1. Traditional Methods: Manual Probing Still Gold Standard

• Periodontal probing (measuring pocket depth, attachment loss, and bleeding) remains the cornerstone of diagnosis.
• Accuracy & Limitations: While manual probes are reliable, reproducibility depends on examiner skill, probe design, and inflammation levels. Electronic probes show promise but haven’t surpassed manual methods.
• Imaging: 2D radiographs (like periapical X-rays) are standard for assessing bone loss, but CBCT(3D imaging) is superior for complex cases (e.g., furcation defects). However, due to radiation and cost, CBCT isn’t recommended for routine use.

2. Biomarkers: Potential but Not Yet Ready for Prime Time

• Microbial markers (e.g., P. gingivalis) and host-derived markers (e.g., MMP-8 in saliva) can distinguish health from periodontitis but lack consistent accuracy for staging/grade differentiation.
• Genomics: While genetic testing helps identify rare forms of periodontitis (e.g., early-onset), it’s not yet useful for common cases due to polygenic complexity.
• Future Hope: Multi-omics (combining genomics, proteomics, etc.) + AI may unlock better diagnostic tools.

3. Emerging Tech: AI & Digital Tools on the Rise

• AI in Dental Clinics:
  • Algorithms analyzing radiographs or photos can detect bone loss and classify disease—sometimes matching expert accuracy.
  • Limitations: Most AI tools are still in development, lack real-world validation, and aren’t yet approved as standalone diagnostics.
• Screening Outside Clinics:
  • Questionnaires (e.g., CDC/AAP) and self-assessed bleeding tests are simple but miss mild cases.
  • AI + Biomarkers: Combining saliva tests (e.g., aMMP-8) with risk factors improves screening for severe periodontitis.

4. Challenges & Future Directions

• Barriers:
  • The 2018 classification system is thorough but complex; clinicians struggle with borderline cases.
  • Biomarker/AI tools need standardization, affordability, and regulatory approval.
• Next Steps:
  • Better datasets: Diverse, high-quality data to train AI.
  • Integration: Tools must fit seamlessly into workflows (e.g., EHRs).
  • Equity: Ensure tech is accessible globally, not just high-resource settings.

Final Thoughts

While manual probing and radiographs remain essential, the future of periodontal diagnosis lies in biomarkers, AI, and digital tools—offering faster, more precise care. However, collaboration among researchers, clinicians, and regulators is key to turning promise into practice.